Worked on configuration

colors.txt

@@ -1,6 +0,0 @@
-65, 65, 65    bai
-0, 0, 0       black
-22, 48, 178   red
-76, 111, 19   green
-
-

test/cv_helper.py

@@ -1,8 +1,12 @@
 import itertools
 from typing import Tuple, List, Dict
+import zipfile
+import io
+import json
+import dataclasses
+
 import numpy as np  # type: ignore
 import cv2  # type: ignore
-import zipfile
 
 from .context import shenzhen_solitaire
 from shenzhen_solitaire.cv import adjustment
@@ -30,52 +34,47 @@ def simplify(image: np.ndarray) -> None:
     cv2.waitKey(0)
     cv2.destroyWindow("Window")
 
+def calibrate(image: np.ndarray) -> None:
+    adj = adjustment.adjust_field(image)
+    squares = card_finder.get_field_squares(image, adj)
+    catalogue = card_finder.catalague_cards(squares)
+    simplified_catalogue = []
+    for square, card in catalogue:
+        simplified_catalogue.append((card_finder.simplify(square), card))
+
+    zip_stream = io.BytesIO()
+    with zipfile.ZipFile(zip_stream, "w") as zip_file:
+        zip_file.writestr('adjustment.json', json.dumps(dataclasses.asdict(adj)))
+
+        file_stream = io.BytesIO()
+        np.save(file_stream, squares[0], allow_pickle=False)
+        print(file_stream.getvalue())
+        zip_file.writestr('0.dat', file_stream.getvalue())
+    print()
+    print(zip_stream.getvalue())
+    with open('myzip.zip', 'wb') as fd:
+        fd.write(zip_stream.getvalue())
+
 
 def main() -> None:
-    #image = cv2.imread("Solitaire.png")
     with open("Solitaire.png", 'rb') as fd:
         img_str = fd.read()
     nparr = np.frombuffer(img_str, np.uint8)
     image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    #image2 = cv2.imread("Solitaire2.png")
-    #image2 = cv2.resize(image2, (1000, 629))
-    image2 = cv2.imread("Solitaire.png")
 
-    adj = adjustment.adjust_field(image)
-    squares = card_finder.get_field_squares(image, adj)
-    print(squares[0])
-    np.save('0.dat', squares[0], allow_pickle=False)
-    assert 0
-    with open("0.dat", 'wb') as fd:
-        fd.write(squares[0].tobytes())
-    catalogue = card_finder.catalague_cards(squares[:5])
-    my_zip = zipfile.ZipFile('myzip.zip', mode='w')
-    for index, x in enumerate(catalogue):
-        my_zip.writestr(f"{index}.dat", x[0].tobytes())
-    my_zip.close()
-    assert 0
+    #print(squares[0])
 
-    squares = card_finder.get_simplified_squares(image, adj)
-    print("Simplified")
-
-    adj.x -= 2
-    adj.y -= 2
-    adj.w += 5
-    adj.h += 5
-
-    image_squares = card_finder.get_field_squares(image2, adj)
-    for i in range(10, 20):
-        image_squares[i], _ = card_finder.simplify(image_squares[i])
-        print("Finding...")
-        found_image, certainty = card_finder.find_square(
-            image_squares[i], squares)
-        print(certainty)
 
 
 def main2() -> None:
-    A = np.load('0.dat.npy')
+    file_stream = None
+    with zipfile.ZipFile('myzip.zip', "r") as zip_file:
+        file_stream = io.BytesIO(zip_file.read('0.dat'))
+
+    A = np.load(file_stream)
     print(A)
 
 
 if __name__ == "__main__":
+    main()
     main2()